Diversity of milk traits in 25 goat breeds

Goats are livestock that is mostly raised by small farmers in Indonesia because they are easier to raise. Apart from having the potential to become meat, several breeds of which are kept as milk-purpose. Milk traits of each breed differ from one another. Therefore, this study tried to observe genetic differences of 25 goat breeds with statistical approach. Information about milk traits from 25 goat breeds is obtained from published journal. Multidimensional preference analysis and average linkage cluster analysis were performed using SAS 9.4 to determine the differences in goat breeds from three traits, namely milk yield, fat content, and protein content. Multidimensional preference analysis was able to see the advantages of breeds from the three observed traits. Goat breeds with superior milk yields are Saanen, Camosciata delle Alpi, and Charmoisée. Sarda Primitiva, Sarda, Etawah Grade have high fat content in milk. In addition, Arsi-Bale and Somali have high protein content. Average linkage cluster analysis is able to observe the genetic relationship of goat breeds based on three traits. According to average linkage cluster analysis, we found four clusters for goat breeds in this study. With existing statistical approaches, we can evaluate genetic diversity in milk traits.

Analyzing the Stressors for Frontline Soldiers Fighting Against Coronavirus Disease 2019 Pandemic

This study aimed to analyze stressors to which medical staff is vulnerable due to the coronavirus disease 2019 (COVID-19) pandemic. It also imposes a hierarchy on complex relations among stressors for excavating underlying structure and builds a model of interrelationships contrasting reality. The design of this study comprises a literature survey, data collection from primary sources, and analysis. Stressors have been explored from within current published/unpublished literature and validated by experts through approval vote. Data were collected from the focus group (panel of experts), and interpretive structural modeling (ISM) was used as the research methodology. Findings of ISM are avowed through “cross-impact matrix multiplication applied to classification” (MICMAC) analysis. As a result of the literature survey, a list of stressors was generated, and a total of 19 stressors qualified as representative of the phenomenon. The results of ISM show that two stressors (i.e., “unavailability of proper personal protective equipment (PPE)” and “lack of proper communication”) emerged as the most critical stressors since they occupy the bottom of the model, whereas, four stressors (i.e., “anxious about isolation/quarantine,” “subject to violent crimes,” “feeling frustrated and powerless,” and “exhausting shifts/hours without clear end”) are relatively less critical since they occupy the top of the model. The rest of the stressors occupy the middle of the model and therefore, have moderate-severe effects on frontline soldiers. The results of MICMAC show that the stressor “subject to violent crimes” is classified in the dependent cluster and the remaining fall in the linkage cluster but no stressor falls in independent and autonomous. Overall results indicate that all stressors are relevant to the phenomenon under this study, but they are currently not settled. This study is invaluable for policymakers, frontline soldiers, researchers, the international community, and society since it provides a lot of new information that is helpful in refining strategies and combating influential stressors.

Performance and character contributions to variability in okra (Abelmoschus esculentus L. Moench) genotypes

Okra is an important vegetable crop, but its optimal production is constrained by a myriad of problems including pests, poor agronomic practices, and improper varietal identification among others. A study was carried out to determine the field performance and contribution of agronomic characters to overall variation in eighteen okra genotypes over two locations, Teaching and Research Farms of the Federal University of Agriculture, Abeokuta, Nigeria and Rehoboth Farms Limited, Moniya, Ibadan, Nigeria. The experiments were laid down in a randomized complete block design with three replicates and data were collected on number of days to emergence, number of days to 50% flowering, number of branches per plant, pod length, pod width, number of pods per plant, plant height, pod weight, number of seeds per pod, number of ridges per pod, 100 seed weight, seed, and pod yield. The data were subjected to analysis of variance, heritability in the broad sense, principal component analysis as well as the single linkage cluster analysis. Results revealed significant (p <0.05) variation in the genotypes and high heritability estimates for most of the characters. Number of branches per plant, plant height, number of pods per plant accounted for the highest contributor to variations in the accessions while clustering analysis revealed genotypes; NGB00303, NGB00342 and NGB00346 were distant from all genotypes making them useful materials for hybridization studies.

Genetic Diversity Assessment in Dolichos Bean (Lablab purpureus L.) Based on Principal Component Analysis and Single Linkage Cluster Analysis

Background: Dolichos bean occupies a unique position among the legume vegetables of Indian origin for its high nutritive value and wider climatic adaptability. Despite its wide genetic diversity, no much effort has been undertaken towards genetic improvement of this vegetable crop. Knowledge on genetic variability is an essential pre-requisite as hybrid between two diverse parental lines generates broad spectrum of variability in segregating population. The current study aims to assess the genetic diversity in dolichos genotypes to make an effective selection for yield improvement.Methods: Twenty genotypes collected from different regions were evaluated during year 2016-17 and 2017-18. Data on twelve quantitative traits was analysed using principal component analysis and single linkage cluster analysis for estimation of genetic diversity.Result: Principal component analysis revealed that first five principal components possessed Eigen value greater than 1, cumulatively contributed greater than 82.53% of total variability. The characters positively contributing towards PC-I to PC-V may be considered for dolichos improvement programme as they are major traits involved in genetic variation of pod yield. All genotypes were grouped into three clusters showing non parallelism between geographic and genetic diversity. Cluster-I was best for earliness and number of cluster/plant. Cluster-II for vine length, per cent fruit set, pod length, pod width, pod weight and number of seed /pod, cluster III for number of pods/cluster and pod yield /plant. Selection of parent genotypes from divergent cluster and component having more than one positive trait of interest for hybridization is likely to give better progenies for development of high yielding varieties in Dolichos bean.

Variability analysis of some genotypes in Nigeria tea (Camellia sinensis) germplasm

Thirty four tea clones were sourced from Cocoa Research Institute of Nigeria tea germplasm and raised through stem cuttings for 10 months in the nursery. The experiment was laid out in a randomized complete block design (RCBD) with 3 replications in 2016. Agronomic and yield data were collected and subjected to analysis of variance. Single linkage cluster analysis (SLCA), principal component analysis (PCA) and FATCLUS analysis were employed to analyse the data. ANOVA showed considerable significant variation p<0.05 among the 34 tea genotypes. The PCA showed that Plant Height (PH) 0.39, Number of Leaves (NL) 0.38, Number of Branches (NB) 0.37, Harvestable Points (HP) 0.31, Stem Diameter 0.39 and Leaf Breadth 0.30 accounted for most of the variations observed. Axes 1, 2 and 3 of the PCA accounted for 37.23%, 15.48% and 10.75% variability respectively with cumulative value of 63.47%. The genotypes were clustered into 7 groups by FASTCLUS Analysis. The dendrogram showed that the first cluster was observed between NGC29 and NGC 47 at 0.08 level of similarity. At 0.50 level of similarity the dendrogram revealed 5 distinct groups. Therefore, variation exists among the tea germplasm in Nigeria thereby suggests further presenting opportunities for further varietal development.

Assessment of Genetic Divergence in Long Day Onion (Allium cepa L.) through Principal Component and Single Linkage Cluster Analysis

To assess the nature and magnitude of genetic diversity in long day onion germplasm by using the principal component analysis and single linkage cluster analysis an experiment was carried out with 34 onion genotypes. High coefficient of variation with wide range in traits indicated an appreciable variability in germplasm. Genotypes were classified into seven principal components having Eigen value > 1, cumulatively accounted for 83.87% of total variability. Principal Component - I contributed for 24.73% of total variation for followed by principal component-II (15.27%). PC-I had high positive loading for bulb weight (0.401), marketable yield (0.338), total bulb yield (0.401) and PC-II had high positive loading for plant height (0.412), PC-III for high T.S.S. (0.276) PC -IV for A grade bulbs (0.436), PC-V for polar diameter of bulbs (0.514), PC-IV negatively loaded with purple blotch (-0.461) and PC-VII for narrow neck thickness (-0 .515). Plotting PC-I aganist PC-II differenciated CITH-O-13, CITH-O-4, CITH-O-22, CITH-O-19, CITH-O-9, CITH-O-6 and CITH-O2 as most divergent genotype.On the basis of single linkage cluster means cluster-I was most importent for average bulb weight, minimum bolters, high marketble bulb percentage high marketable and total bulb yield whereas cluster -II was important for maximum nuber of leaves/plant and minimum neck thicknes. Highest inter-cluster distance was observed between cluter II and Cluster-I(873.5% ).Most divergent genotypes with high inter cluter distance could be the most appropriate parents for crop impovement in onion.

The orbital clusters among the near-Earth asteroids

ABSTRACT Fifteen orbital clusters (associations) were identified among ${\sim }20\, 000$ near-Earth asteroids (NEAs). All associations were found with a high statistical reliability using a single linkage cluster analysis algorithm and three orbital similarity functions. The identified groups constitute a small fraction (4.74 per cent) of the entire sample. Notwithstanding, they may be hazardous to Earth and its inhabitants. As with meteoroid streams, every year Earth comes very close to the orbits of each association. In two cases (2008TC3 and 2017FU102), the distance between the asteroid’s orbit and Earth’s orbit was shorter than Earth’s radius. Among the members of the identified associations, we found 331 objects larger than the Chelyabinsk asteroid and all of them approach Earth’s orbit at a distance smaller than 0.05 au. Two of the identified groups, (4179) Toutatis and (251430) Itokawa, support the hypothesis regarding the catastrophic origins of the asteroids Toutatis and Itokawa through violent collisions. This study does not focus on the origin of the NEA associations, but rather focuses on tracing the associations. Regardless of their origin, the identified groups pose a serious threat to Earth. Hence, to facilitate their monitoring of we calculated coordinates of the theoretical radiants and the calendar dates of their potential activity.

Clustering Provinces in Indonesia based on Community Welfare Indicators

The Preamble of the 1945 Constitution of the Republic of Indonesia explicitly states that the main task of the government of the Republic of Indonesia is to advance general prosperity, to develop the nation's intellectual life, and to realize social justice for all Indonesian people. Social inequality is a problem that is still faced by Indonesian people today. To solve the problem required supporting data analysis as a basis for policy formulation. This research was conducted with the aim of clustering provinces in Indonesia based on community welfare indicators using K-Means cluster analysis. K-Means cluster analysis is chosen based on the variance value (0.101), which is smaller than the variance value in the average linkage cluster analysis (0.152). Based on data analysis, provinces in Indonesia are clustered into three where the first cluster consists of 21 provinces, the second cluster consists of 3 provinces, and the third cluster consists of 10 provinces. Each cluster has different characteristics that can be of concern to the parties concerned to overcome the social welfare gap. Besides, in order cluster results are more easily understood, visualization of results is added with a Geographic Information System (GIS) using Indonesian maps accompanied by differences in color gradations for each cluster